biostudies-literatureTan MCNIDDK NIH HHSNational Institute of Diabetes and Digestive and Kidney DiseasesCaroline Wiess Law Fund for Research in Molecular MedicineU.S. Department of Veterans Affairs4500-4508https://www.ebi.ac.uk/biostudies/studies/S-EPMC9117573biostudies-literatureUnknown67(9)<h4>Background/aims</h4>Screening for gastric intestinal metaplasia (GIM) may lead to early gastric cancer detection. We developed and validated a pre-endoscopy risk prediction model for detection of GIM based on patient-level risk factors in a U.S.<h4>Population</h4><h4>Methods</h4>We used data from 423 GIM cases and 1796 controls from a cross-sectional study among primary care and endoscopy clinic patients at the Houston VA. We developed the model using backwards stepwise regression and assessed discrimination using area under the receiver operating characteristic (AUROC). The model was internally validated using cross-validation and bootstrapping. The final expanded model was compared to a model including H. pylori infection alone and a baseline model including remaining terms without HDigestive diseases and sciencesRisk Score Using Demographic and Clinical Risk Factors Predicts Gastric Intestinal Metaplasia Risk in a U.S. Population.PMC9117573CIN 13-413P30 DK056338Liu YThrift APTan MCNguyen THEl-Serag HBHo QfalseRisk Score Using Demographic and Clinical Risk Factors Predicts Gastric Intestinal Metaplasia Risk in a U.S. Population.<h4>Background/aims</h4>Screening for gastric intestinal metaplasia (GIM) may lead to early gastric cancer detection. We developed and validated a pre-endoscopy risk prediction model for detection of GIM based on patient-level risk factors in a U.S.<h4>Population</h4><h4>Methods</h4>We used data from 423 GIM cases and 1796 controls from a cross-sectional study among primary care and endoscopy clinic patients at the Houston VA. We developed the model using backwards stepwise regression and assessed discrimination using area under the receiver operating characteristic (AUROC). The model was internally validated using cross-validation and bootstrapping. The final expanded model was compared to a model including H. pylori infection alone and a baseline model including remaining terms without H2022-01-01T00:00:00Z2022 Sep2025-04-04T20:41:33.757Z2025-04-04T20:41:33.757ZS-EPMC91175733479744710.1007/s10620-021-07309-3